Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
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Lightning talks: Advances in fairness in AI: From research to practice
Over the past few years, we’ve seen that artificial intelligence (AI) and machine learning (ML) provide us with new opportunities, but they also raise new challenges. Most notably, these challenges have highlighted the various ways…
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Panel: The future of reinforcement learning
This panel brings together a variety of experts from industry and academia to discuss the question, what is the future of reinforcement learning? Reinforcement learning is an important research area in AI currently, and it…
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Tutorial: Best practices for prioritizing fairness in AI systems
As artificial intelligence (AI) continues to transform people’s lives, new opportunities raise new challenges. Most notably, when we assess the societal impact of AI systems, it’s important to be aware of their benefits, which we…
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Demo: Generating formally proven low-level parsers with EverParse
Speaker: Aseem Rastogi, Principal Researcher, Microsoft Research India DARPA and MITRE estimate that 80 percent of software security vulnerabilities have incorrect input validation as their root cause. In such scenarios, attackers provide malformed input, which,…
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Research talk: Challenges in multi-tenant graph representation learning for recommendation problems
Recent research has shown that representations learned from user-user and user-item graphs can be used to improve recommendation performance. In this research, the recommendation model is often trained with representation learning. In project DEEGO, we…
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Panel discussion: Content moderation beyond the ban: Reducing borderline, toxic, misleading, and low-quality content
Public debate about content moderation focuses almost exclusively on removal, such as what is deleted and who is suspended. But what about content that is identified as “borderline,” which almost—but not quite—violates the guidelines? Faced…
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Research talk: Bucket of me: Using few-shot learning to realize teachable AI systems
We’re entering a technological era that is all about “me”—from personalized shopping recommendations to avatars, and even bespoke healthcare treatments. Deeper inspection of artificial intelligence (AI) systems, however, reveals that “me” is not really me.…
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Research talk: Multidimensional analysis of cloud-native software based on large-scale operation data
Dynamic and static analysis of source code has been widely used in software development practices for purposes such as reverse engineering, design issue detection, and fault localization. Cloud-native software, which is featured by containerized and…
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Research talk: SPTAG++: Fast hundreds of billions-scale vector search with millisecond response time
Current state-of-the-art vector approximate nearest neighbor search (ANNS) libraries mainly focus on how to do fast high-recall search in memory. However, extremely large-scale vector search scenarios present certain challenges. For example, hundreds of billions of…
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Fireside chat: Opportunities and challenges in human-oriented AI
A key challenge in developing novel AI technology is to ensure that resulting approaches and their applications fit well within the human environments they will be applied in. Recent research at Microsoft develops new approaches…
